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Journal of the American College of Nutrition, Vol. 24, No. 3, 158-165 (2005)
Published by the American College of Nutrition

Strategies for Healthy Weight Loss: From Vitamin C to the Glycemic Response

Carol S. Johnston, PhD, FACN

Department of Nutrition, Arizona State University, Mesa, Arizona

Address reprint requests to: Carol S. Johnston, PhD, FACN, Department of Nutrition, Arizona State University East, 7001 E. Williams Field Rd., Mesa, AZ 85212. E-mail: carol.johnston{at}asu.edu


   ABSTRACT
TOP
 ABSTRACT
Introduction
 Vitamin C Status
 Macronutrient Profile of Diet
 Glycemic Response to Meals
 Conclusion
 ACKNOWLEDGMENTS
 References
 
Abstract America is experiencing a major obesity epidemic. The ramifications of this epidemic are immense since obesity is associated with chronic metabolic abnormalities such as insulin resistance, dyslipidemia, and heart disease. Reduced physical activity and/or increased energy intakes are important factors in this epidemic. Additionally, a genetic susceptibility to obesity is associated with gene polymorphisms affecting biochemical pathways that regulate fat oxidation, energy expenditure, or energy intake. However, these pathways are also impacted by specific foods and nutrients. Vitamin C status is inversely related to body mass. Individuals with adequate vitamin C status oxidize 30% more fat during a moderate exercise bout than individuals with low vitamin C status; thus, vitamin C depleted individuals may be more resistant to fat mass loss. Food choices can impact post-meal satiety and hunger. High-protein foods promote postprandial thermogenesis and greater satiety as compared to high-carbohydrate, low-fat foods; thus, diet regimens high in protein foods may improve diet compliance and diet effectiveness. Vinegar and peanut ingestion can reduce the glycemic effect of a meal, a phenomenon that has been related to satiety and reduced food consumption. Thus, the effectiveness of regular exercise and a prudent diet for weight loss may be enhanced by attention to specific diet details.

Key words: weight loss, vitamin C, high-protein diets, vinegar, peanuts

Key teaching points:

• Gene polymorphisms associated with biochemical pathways that regulate fat oxidation, energy expenditure, or energy intake have been linked to genetic susceptibility to obesity.

• 30–70% of the variation in body weight and fat mass can be attributed to genetics; environmental conditions, including specific dietary factors, may play a pronounced role in the expression of these phenotypes.

• Vitamin C status is associated with tissue carnitine concentrations and fat oxidation and may represent a modifiable condition that would impact fat oxidation thereby affecting body composition and body mass.

• The thermic effect of food, which accounts for ~10% of daily energy expenditure, is related to dietary protein; thus, the greater calorie-cost of high-protein diets, in association with the increased satiety of these diets, may protect against gradual weight gain.

• The glycemic response to food ingestion has been associated with subsequent hunger; complementary foods, such as vinegar or peanut products, when added to meals, may attenuate meal-time glycemia promoting satiety and reduced energy intake.


   Introduction
TOP
 ABSTRACT
 Introduction
Vitamin C Status
 Macronutrient Profile of Diet
 Glycemic Response to Meals
 Conclusion
 ACKNOWLEDGMENTS
 References
 
America is experiencing a major epidemic of overweight and obesity. In 2001–02, 66% of adults were overweight (body mass index [BMI] ≥25) and 31% of adults were obese (BMI ≥30) [1]. In comparison, the prevalences of overweight and obesity respectively were 46% and 15% in 1976–80 and 56% and 23% in 1988–94 [2]. Excess weight is associated with the leading causes of death in the U.S.: cardiovascular disease, cancer, stroke, and type 2 diabetes. In fact, obesity is quickly gaining on tobacco as the leading cause of preventable death in the U.S. In 1993, tobacco contributed to 400,000 deaths annually versus the 300,000 deaths attributed to diet and inactivity [3]. By the year 2000, the gap had narrowed considerably with 435,000 deaths annually attributed to tobacco and 400,000 deaths attributed to diet and inactivity [4]. As a sign of the times, Medicare recently announced that it had changed its policy and will recognize obesity as an illness permitting coverage for some obesity treatments. Hence, the ramifications of the obesity epidemic are immense, from the increased risk of debilitating conditions and death, to the tremendous economic burden placed on America’s healthcare system.

The Dietary Guidelines for Americans reflect the preponderance of the research evidence for effective strategies for weight loss and weight maintenance: be physically active each day; choose a variety of grains daily, especially whole grains; and choose a diet that is low in saturated fat and cholesterol and moderate in total fat [5–9]. However, 30–70% of the variation in body weight and fat mass can be attributed to genetics [10–12]; and the impact of a prudent diet and/or physical activity varies considerably between overweight individuals [13]. Loos and Bouchard [14] described a three-tier model for genetic susceptibility for obesity and postulated that the environment has a permissive role in the severity of the obesity phenotype. According to this model, at least 5% of the obesity cases represent genetic obesity minimally impacted by the environment. The more common forms of obesity would fall into categories with either a strong or slight predisposition to obesity, and environmental conditions would play a pronounced role in the expression of the phenotype. Thus, in a restrictive environment where food availability and labor saving devices are limited (similar to the adoption of a prudent diet and exercise program), many individuals with a genetic predisposition to obesity would likely be normal weight or slightly overweight. But most Americans live in an ‘obesogenic’ environment, and although some obese-promoting environmental conditions have been identified, it is reasonable to expect that there are other modifiable conditions impacting the obesity phenotype. Attention to such variables may permit the fine-tuning of weight loss strategies and promote greater successes.

Much of the work to understand the genetic susceptibility to obesity has been to identify gene polymorphisms associated with the biochemical pathways that regulate fat oxidation, energy expenditure, or energy intake. Several proteins involved in these pathways have been extensively studied: fatty acid synthase, the mitochondrial uncoupling proteins, the ß- and {alpha}2-adrenoceptors, leptin, and the leptin receptor [15–19]. We have identified several dietary factors that also appear to modify energy expenditure and energy intake. Tweaking these dietary factors to promote fat oxidation, energy expenditure, or reduce energy intake may lessen the impact of a hedonistic environment on the obesity phenotype.


   Vitamin C Status
TOP
 ABSTRACT
 Introduction
 Vitamin C Status
Macronutrient Profile of Diet
 Glycemic Response to Meals
 Conclusion
 ACKNOWLEDGMENTS
 References
 
About 20% of U.S. adults are vitamin C depleted, plasma concentrations 11–28 µmol/L, and 12–17% are vitamin C deficient and at risk of clinical scurvy, plasma concentrations <11 µmol/L [20,21]. Twenty-five years ago, the prevalence of vitamin C deficiency was much lower, 3–5% of U.S. adults [22]. Correspondence among physicians suggest that the incidence of scurvy may indeed be on the rise [23,24], a seeming paradox given the wide availability of fresh fruits and vegetables and the addition of vitamin C to many processed foods. Yet, vitamin C in foods is irreversibly oxidized by exposure to light, oxygen, and/or heat, and reports suggest that fresh produce or juice may lose 50–100% of its vitamin C content due to handling and processing [25–27]. Hence, the increased processing of the food supply may be impacting the level of dietary vitamin C available to consumers.

As an effective reducing agent and electron donor, vitamin C has an essential role in numerous metabolic pathways, most notably that of collagen synthesis. Vitamin C is required for the post-translational modification of procollagen polypeptides to form the resilient, cross-linked collagen molecule [28]. Most of the physiological symptoms attributed to scurvy (subcutaneous and intramuscular hemorrhages, leg edema, joint pain, and neuropathy) are related to defective collagen synthesis. Yet, as reported by James Lind in 1753: "the first indication of the approach of this disease is...a pale and bloated complexion; with a listlessness to action or an aversion to any sort of exercise...degenerates soon into a universal lassitude...much fatigue and upon that occasion subject to breathlessness or panting. And this lassitude, with a breathlessness upon motion, are observed to be among the most constant concomitants of the distemper". Vitamin C is required for the biosynthesis of carnitine, a small molecule responsible for shuttling long chain fatty acids across the mitochondrial membrane for ß-oxidation and subsequent fat oxidation [29,30]. Reduced tissue carnitine, and the associated impact on fat oxidation, is considered the cause of the fatigue of scurvy [31,32].

We have observed that individuals with poor vitamin C status (n = 15; plasma vitamin C <34 µmol/L) oxidize less fat during a submaximal walking test than individuals with adequate vitamin C status (n = 7; plasma vitamin C ≥34 µmol/L) (respiratory exchange ratio, RER: 0.87 ± 0.01 versus 0.83 ± 0.01, p < 0.05) (unpublished data). Furthermore, fat energy expended in these subjects was inversely correlated with plasma carnitine (r = –0.489, p = 0.043) and with fatigue as determined by the POMS (Profile of Moods States) questionnaire (r = –0.611, p = 0.009). We conducted a placebo-controlled depletion-repletion trial to determine the impact of vitamin C status on exercise performance and vigor [33]. Subjects with low vitamin C status (4 men and 5 women; 27.6 ± 2.5 y; plasma concentrations <28 µmol/L) consumed a placebo capsule daily for three weeks (depletion period) and an identical looking capsule containing 500 mg vitamin C for the following two weeks (repletion period). Subjects were unaware of their vitamin C status and of the nature of the trial. At the end of trial weeks 3 and 5, subjects completed a low intensity, 90 minute walk at 50% VO2 max, and work efficiency was calculated as [work rate (kcals/min)/energy expended (kcal/min)] x 100.

In the vitamin C repleted state, subjects performed 10% more work at 50% VO2 max equating to a 14% improvement in work efficiency (Table 1). Whether this improvement in vigor and work performance was attributed to increased tissue carnitine concentrations is not known since muscle biopsies were not taken. However, plasma carnitine concentrations did drop nearly 20% (p = 0.05) indicating a rise in muscle carnitine. (In humans, carnitine synthesis from {gamma}-butyrobetaine is restricted to liver, brain, and kidney, and the transport of carnitine into the muscle is dependent on a 1:1 exchange process with {gamma}-butyrobetaine that is synthesized in muscle tissue, a vitamin C-dependent process [34,35]. Hence, in vitamin C depletion, carnitine is trapped in plasma and plasma carnitine concentrations rise [36].)


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  		Table 1. Effect of Vitamin C Status on Blood Indices and on Heart Rate, Substrate Utilization and Aerobic Function during Submaximal Exercise1

 
To examine the effect of vitamin C status on substrate oxidation specifically, we recruited eleven sedentary individuals with poor vitamin C status (plasma vitamin C concentration <34 µmol/L). Subjects were free living and maintained their usual dietary patterns; however, they were instructed not to consume certain fruits, vegetables, and juices, mainly orange juice, oranges, strawberries, melons, broccoli, tomatoes, and peppers (i.e. foods containing >30 mg of vitamin C per serving). During trial weeks 1–4 all subjects consumed a placebo capsule daily (washout). Subjects were then randomized to the repleted group (n = 6; 500 mg vitamin C daily; capsule identical in appearance to placebo) or the depleted group (n = 5; placebo daily). At the end of trial weeks 4 and 8, subjects completed a 60-min submaximal treadmill walking test. Fat energy expended during exercise at week 8 was significantly raised in repleted subjects as compared to depleted subjects (2.03 ± 0.02 and 0.48 ± 0.11 kcals/kg, p = 0.031) (Table 2). RER was slightly lower in repleted subjects as compared to depleted subjects at week 8 (0.879 ± 0.018 and 0.937 ± 0.026 respectively, p = 0.096). Plasma carnitine did not differ by group at week 8 (Table 2); however, plasma vitamin C and carnitine were weakly inversely related (r = –0.441, p = 0.087). Plasma vitamin C was correlated to fat energy expenditure (r = 0.655, p = 0.006) (Fig. 1); thus, vitamin C status explained 43% of the variation in fat oxidation during submaximal exercise.


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  		Table 2. Metabolic Indices in Subjects with Poor Vitamin C Status (Placebo-Controlled Washout; Trial Week 4) Who Were Randomly Assigned to One of Two Treatment Groups: Repleted (N = 5; 500 Mg Vitamin C Daily) or Depleted (N = 3; Placebo Daily)1

 


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  		Fig. 1. Relationship between plasma vitamin C and fat oxidation during submaximal exercise.

 
Together these data provide preliminary evidence that vitamin C status influences fat oxidation, exercise performance, and vigor. Since impaired fat oxidation has been implicated in the development of obesity and in failed weight loss attempts [37–39], vitamin C depletion may create a metabolic perturbation that could potentially impact body mass. Several studies have reported a significant inverse relationship between plasma vitamin C concentrations and degree of obesity [40,41]. In our trials, a weak inverse relationship was noted for plasma vitamin C and body mass (r = –0.36; p = 0.10). Interestingly, a randomized, double blind trial demonstrated that vitamin C supplementation was associated with significantly greater weight loss versus placebo (2.53 kg versus 0.95 kg) after 6 weeks [42]. Thus, vitamin C status may represent a modifiable condition that would impact the expression of the obesity phenotype.


   Macronutrient Profile of Diet
TOP
 ABSTRACT
 Introduction
 Vitamin C Status
 Macronutrient Profile of Diet
Glycemic Response to Meals
 Conclusion
 ACKNOWLEDGMENTS
 References
 
The thermic effect of food (TEF) accounts for roughly 10% of daily energy expenditure. TEF is the increment in energy expenditure above resting values that occurs following food intake. TEF encompasses the obligatory energy costs of ingesting, digesting, absorbing, and metabolizing food and the facultative energy cost related to the disposal of excess, non-essential energy [43]. This latter component of TEF is influenced by autonomic nervous function, which may be modulated by genotype [44,45]. A defect in postprandial thermogenesis would favor weight gain, and a 25–60% reduction in TEF has been reported in obese individuals as compared to their lean counterparts [46,47].

Due to the high metabolic cost of metabolizing protein, dietary protein can exert up to three times more TEF than isocaloric amounts of carbohydrate or fat [48]. We compared the daylong energy-cost of a high-protein, low-fat (HPLF) diet to that of a high-carbohydrate, low-fat (HCLF) diet in young healthy, lean women (n = 10; 19.0 ± 0.4 y; 64.4 ± 2.4 kg) [49]. Subjects consumed each of the two experimental diets, which were composed of common foods and meal plans, in a randomized crossover manner, and metabolic testing was separated by 4-week intervals to control for possible confounding effects of menstrual cycle on energy expenditure. The fasting, morning energy expenditure was similar by diet, 1359 ± 59 and 1396 ± 53 kcals/24/h for the HPLF and HCLF diets respectively. Postprandial energy expenditure at 2.5 h post-meals was 8, 8, and 14 kcals/h higher on the HPLF diet plan as compared to the HCLF diet plan for the breakfast, lunch, and dinner meals respectively (Fig. 2). Assuming that this same energy differential was maintained for 2–3 h intervals post-meals, the higher TEF associated with the HPLF diet would represent an added energy cost of 60–90 kcals/d equating to a loss of ~1 kg every 12–24 weeks (or 2–4 kg/y). Short-term investigations (6–12 weeks) have reported similar weight loss in overweight subjects randomized to energy-restricted, low-fat diets either high (30% energy) or low (15% energy) in dietary protein [50,51]; yet, over longer periods of time, the modest effect of dietary protein on TEF may promote greater weight losses or protect against gradual weight gain.



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  		Fig. 2. Postprandial thermogenesis (difference between post-meal energy expenditure and baseline energy expenditure) in young, healthy women after ingestion of high-protein, low-fat (HPLF) meals versus high-carbohydrate, low-fat (HCLF) meals. Values are means ± SE; asterisks denote significant difference by diet (p < 0.05; repeated measures ANOVA). (Adapted from [49]).

 
Dietary protein is also the macronutrient generally associated with increased satiety [52]; yet, mechanisms controlling satiety are not clear [53]. The thermic effect of protein has been related to satiety [54], possibly due to the obligatory oxidative disposal of amino acids. Dietary protein also is a potent stimulator of the gastrointestinal hormones cholecystokinin and glucagon-like peptide [55], both important mediators of satiety via effects on gastrointestinal functions. Voluntary reductions in energy consumption are noted in subjects consuming high-protein meals ad libitum as compared with high-carbohydrate meals [56,57]. Furthermore, in short-term trials, energy consumption at subsequent meals was significantly less in subjects consuming high-protein versus high-carbohydrate preloads [57,58]. During a strictly controlled 6-wk weight loss trial comparing a high-protein, low-fat, calorie restricted diet to a high-carbohydrate, low-fat, calorie restricted diet [51], we asked subjects to indicate on a 7-point Likert-scale (extremely hungry to extremely full) how they generally had felt over the past week. The experimental diets were equally effective at reducing body weight and fat mass, but the HPLF subjects reported feeling more satiated in the first 4 weeks of the feeding trial compared with HCLF subjects (Fig. 3). Moreover, 20% of the subjects randomized to the HCLF diet were dropped from the trial since they were unable to comply with the calorie restrictions due to unendurable hunger.



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  		Fig. 3. Perceived satiety for subjects consuming high-protein (HPLF, n = 9) or high-carbohydrate (HCLF, n = 7) low-fat, energy-restricted diets for 6 weeks using a 7-point Likert scale. Values are means ± SE. (Adapted from [51]).

 
Thus, dietary protein may represent a dietary factor that can be manipulated to influence the obesity phenotype via effects on energy expenditure and energy intake. In this view, the recent successes attributed to low-carbohydrate, high-protein (Atkins-like) diets may simply reflect the thermogenesis and the greater satiety afforded by higher intakes of protein and not the ‘very low carbohydrate’ nature of the diets [59,60].


   Glycemic Response to Meals
TOP
 ABSTRACT
 Introduction
 Vitamin C Status
 Macronutrient Profile of Diet
 Glycemic Response to Meals
Conclusion
 ACKNOWLEDGMENTS
 References
 
The current American diet is composed mainly of carbohydrates (50% total energy) [61], and carbohydrate-containing foods are differentiated by their glycemic index (GI), an estimate of the magnitude of the blood glucose response following food ingestion. As compared to high-GI foods (processed grains, foods composed of white flour, potato products, and sweets), low-GI foods (whole grains, fruits, vegetables, dairy products, and legumes) benefit body weight regulation by promoting satiety. Of 20 studies published between 1977 and 1999, 16 demonstrated that low-GI foods promoted post-meal satiety and/or reduced subsequent hunger [62]. In children attending an outpatient pediatric obesity program, patients who followed a low-GI diet lost significantly more weight after 4 months than patients who followed a reduced-fat diet (change in body weight, –2.03 kg versus +1.31 kg, p <0.05) [63]. Thus, a reduction in the meal-time glycemic load (GL; GI x g total carbohydrate) is associated with reduced energy consumption and weight loss; and, this strategy may represent an important approach to the prevention and treatment of obesity [64,65].

We have examined the possibility of complementary foods to reduce postprandial glycemia and to enhance satiety. This approach is simpler than approaches that would require dietary change. Preliminary work in our laboratories has indicated that vinegar [66] and peanut product consumption at mealtime reduced the glycemic response to meals. Eleven healthy adults (27.9 ± 2.9 y; body mass index, 22.7 ± 1.0 kg/m2) consumed two different test meals (bagel and juice, GL = 81; or teriyaki chicken on rice, GL = 48) in random order under three different experimental treatments: control, vinegar, and peanut. Water sweetened with saccharine (60 g) was consumed pre-meal for the control and peanut treatments, and a similarly sweetened diluted vinegar drink was consumed pre-meal for the vinegar treatments. For the peanut treatment, peanut butter (25 g) was substituted for butter in the bagel and juice meal, and roasted peanuts (25 g) were substituted for butter in the teriyaki meal. These changes did not alter the GL of the meals.

Vinegar or peanut ingestion reduced the 60-min glucose response (calculated as the incremental area-under-the-curve) to either test meal by 50–55% (Fig. 4). After consumption of the bagel and juice meal, energy consumption for the remainder of the day was weakly affected by the vinegar and peanut treatments (–12 to –16% or a reduction of ~200–275 kilocalories; p = 0.111) (Fig. 5). Later energy consumption did not vary by treatment when the teriyaki chicken test meal was consumed, perhaps a reflection of the lower GL of this meal. Regression analysis indicated that the 60-min glucose response to the test meals explained 11 to 16% of the variation in later energy ingestion (p < 0.05). The acetic acid in vinegar may reduce the glycemic response to high GL foods by inhibiting disaccharidases in the small intestinal epithelium [67] or by stimulating glucose uptake and utilization in peripheral tissues [68]. Peanuts contain high levels of the amino acid arginine which is a potent insulin secretagogue [69,70]; thus, peanut consumption may affect glycemia by rapid stimulation of insulin release and glucose uptake. These data indicate that the addition of vinegar or peanut products to a high-GL meal reduces postprandial glycemia.



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  		Fig. 4. Postprandial blood glucose concentrations depicted as incremental area-under-curve (trapezoidal rule) for each experimental condition. Values are means ± SE; asterisks indicate significant difference from control value (multivariate general linear model for repeated measures).

 


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  		Fig. 5. Dietary energy ingestion following the consumption of two test meals (bagel and juice meal [GL = 81], dark bars; or teriyaki chicken on rice meal [GL = 48], open bars) under three experimental conditions: control, peanut, vinegar. Dietary energy encompasses all foods and beverages consumed for the entire day excluding the test meal. Values are means ± SE (n = 11); p values represent multivariate general linear model for repeated measures.

 
Long-term trials would determine whether this simple concept of complementary foods to attenuate postprandial glycemia would favorably impact the obesity phenotype. Unpublished data from our laboratories indicated that subjects randomized to receive vinegar daily (n = 12; 2 Tbls red raspberry vinegar twice daily) lost weight after 4 weeks as compared to a slight weight gain in the control subjects (n = 10; 2 Tbls cranberry juice twice daily), –0.72 ± 0.24 kg and +0.27 ± 0.32 kg respectively (p = 0.020). Interestingly, epidemiologic trials designed to examine the benefits of regular nut consumption on cardiovascular disease risk have indicated an inverse association between frequency of nut consumption and body mass index [71], an effect possibly related to enhanced satiety [72].


   Conclusion
TOP
 ABSTRACT
 Introduction
 Vitamin C Status
 Macronutrient Profile of Diet
 Glycemic Response to Meals
 Conclusion
ACKNOWLEDGMENTS
 References
 
A slight to strong genetic predisposition for obesity likely exists for many individuals, a result of susceptibility alleles at a number of loci rather than a specific gene mutation. Hence the environment plays a key role in the permissive expression of obesity phenotypes. The identification of easily manipulated dietary factors (i.e., nutrient supplements or complementary foods) that affect biochemical pathways involved in fat oxidation, energy expenditure, or energy intake, would lay the basis for new adjunct therapies for body weight management. We have preliminary evidence suggesting that the regular ingestion of vitamin C supplements, dietary protein, vinegar, and/or nuts may help stimulate energy expenditure, promote satiety, and/or modulate fat production. Thus, the effectiveness of regular exercise and a prudent diet for weight loss may be enhanced by attention to specific diet details.


   ACKNOWLEDGMENTS
TOP
 ABSTRACT
 Introduction
 Vitamin C Status
 Macronutrient Profile of Diet
 Glycemic Response to Meals
 Conclusion
 ACKNOWLEDGMENTS
References
 
I am grateful to my long-time friend and colleague, Pamela Swan, for her expertise in obesity and energy expenditure, and I am indebted to the staff of the Department of Nutrition at Arizona State University East, particularly our research technician and phlebotomist, Michael Stroup. Funding for much of this work was from the Lloyd S. Hubbard Nutrition Research Fund of the Arizona State University Foundation.

Received July 27, 2004. Accepted February 8, 2005.


   References
TOP
 ABSTRACT
 Introduction
 Vitamin C Status
 Macronutrient Profile of Diet
 Glycemic Response to Meals
 Conclusion
 ACKNOWLEDGMENTS
 References
 

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